Measuring health in hard-to reach populations. Lecture 5

1.

Lecture 5
Measuring health in hard-to reach
populations
Social Studies of Health 27/11/20

2.

Sampling and recruitment
◉ Sampling and recruitment is always an issue
◉ Hard-to reach populations
○ No sampling frame (not institutionalized)
○ Not willing to disclose the group membership
(stigma + threats)
○ Might be of special interests for the health research
due to the health risks
○ Ignoring leads to no action

3.

Why traditional things
wouldn’t be helpful?
◉ Subpart of representative sample?
○ Telephone interviews (CATI) to find people who
inject drugs/illegal migrants etc?

4.

Why traditional things
wouldn’t be helpful?
◉ Subpart of representative sample?
○ Telephone interviews (CATI) to find people who
inject drugs/illegal migrants etc?
○ More non-response
○ Not covered by “representative sample” – no
phone, other places to live, rarely at home
○ Sensitive question (SDB/intrusiveness/threat of
disclosure)

5.

Two approaches
Chain-referral
Members of the target group are
well-connected and are willing to
recruit each other
“Passive”
Location
Majority of target group is
systematically concentrated in
identifiable places and could be
recruited by the researchers there
“Active”
картинка
http://rusaids.net

6.

Chain-referral
◉ Snow-ball sampling
◉ Chain-referral sampling
◉ Respondent-driven sampling

7.

Respondent-driven sampling
Heckathorn, Douglas D. 1997." Respondent-Driven
Sampling: A New Approach to the Study of Hidden
Populations." Social Problems.
Heckathorn, Douglas D. 2002." Respondent-Driven
Sampling II: Deriving Valid Population Estimates from
Chain-Referral Samples of Hidden Populations." Social
Problems.

8.

Recruitment process and
associated terms
Source: Johnston, L & K. Sabin (2010) Sampling Hard to Reach Populations. Methodological Innovations 5(2), 38-48

9.

Recruitment process and
associated terms
Limited N of initial seeds
Limited options for recruitment (f.ex. up to 3)
Incentives for recruitments
Options for tracking the recruitment chains
Options for statistical correction of associated
biases

10.

Respondent-driven sampling

11.

RDS Methods
Type of chain referral sampling to reach hidden
populations
Begin with a set of non randomly selected seeds
Seeds recruit peers, who recruit peers, etc.
Recruits are linked by coupons with unique
identifying numbers
Recruitment quota through coupons
Incentives provided for completed survey and for
each successful recruit
Heckathorn 1997; Heckathorn & Salganik, 2004; Broadhead et al. 1998

12.

Wave 1 Wave 2 Wave 3 Wave 4
Seed
Wave 5

13.

Wave 1 Wave 2 Wave 3 Wave 4
Markov Process
Wave 5

14.

Wave 1 Wave 2 Wave 3 Wave 4
Markov Process
Wave 5

15.

Wave 1 Wave 2 Wave 3 Wave 4
Markov Process
Wave 5

16.

Wave 1 Wave 2 Wave 3 Wave 4
Markov Process
Wave 5

17.

Important Terms-RDS Methods
◉
◉
◉
◉
◉
Seeds
Wave
Chain
Primary incentive
Secondary incentive

18.

Steps involved in RDS
◉ Begin with a set of non randomly selected
seeds
◉ Seeds recruit peers, who recruit peers,
etc.
◉ Recruits are linked by coupons with
unique
identifying numbers
◉ Incentives provided for completed survey
and for each successful recruit

19.

The Theory Behind RDS
Uses principles of First OrderMarkov Theory
◉ Long referral chains
◉ Final sample will be independent of those
selected as “seeds”
◉ Final sample will be similar to the population
of the network from which you are recruiting

20.

You cannot do RDS If:
The members of your target population
ARE NOT well networked (need some
formative research)
The members of your target population are
TOO stigmatized and afraid to go to your
RDS interview site

21.

Information that MUST be gathered during RDS
◉ Personal Network Size (Degree) - Number
of people the respondent knows within the
target population.
◉ Respondent's Coupon Number - Coupon
number of the respondent.
◉ Respondent's Recruiting Coupon Numbers Coupon numbers respondent used to
recruit others.

22.

Female Sex Workers – Vietnam, 2004
Johnston L et al. J Urban Health , 2006

23.

Recruitment chain starting with a Gay seed
(Seed #6, N=105), Dhaka, Bangladesh, 2006
Johnston L et al. AIDS and Behavior, 2008

24.

Respondent-driven sampling

25.

RDS Assumptions and Requirements
Proportions will eventually reach
equilibrium
Connections are reciprocal
Recruitment is occurring with same
efficiency throughout the population
The population from which a sample is
gathered is infinitely large
Participants’ social network is sufficiently
well connected

26.

RDS Assumptions and Requirements (cont.)
Recruitment is non preferential
Recruits are selected with probability
proportional to their network size (recruiters
with large network sizes are more likely to find
someone
to recruit)
Recruits report their network size with
accuracy sufficient for RDS analysis

27.

◉ http://www.respondentdrivensampling.org/
main.htm
◉ RDSAT (statistical corrections)

28.

◉ QUESTIONS?

29.

Two approaches
Chain-referral
Members of the target group are
well-connected and are willing to
recruit each other
“Passive”
Location
Majority of target group is
systematically concentrated in
identifiable places and could be
recruited by the researchers there
“Active”
картинка
http://rusaids.net

30.

Locations-based
◉
◉
◉
◉
◉
Kind of cluster
Time-location Sampling (TLS)
Venue Day Time Sampling (VDT)
Temporal Spatial Sampling (TSS)
Time Venue Sampling (TVS)

31.

History
◉
Find and recruit from places
(Watters & Biernaki (1989)), venue-based sampling
◉ +
estimation of N in each place (Carlson, Wang, Siegal,
Falck, & Guo (1994) proportional quota sampling)
◉
◉
+ randomization
+ adjusting for time
TLS (Lemp., et. al., 1994; MacKellar et al., 1996)

32.

When to use
◉ Group is visible
◉ Group is concentrated somewhere
◉ We could get there
◉ Absolute majority of this group use those places

33.

◉ •The mapped “universe” is inclusive of the
diversity of the target population
◉ •Members of target population have a chance
of being sampled that is approximately
known, equal, or can be adjusted for
◉ •Random selection of venue, day, and time
minimizes some of the biases of convenience
sampling

34.

◉
◉
◉
◉
◉
Recruit eligible persons at VDT (variations):
–Consecutively
–Systematically
–Proportionately
–Randomly

35.

IVHUB.IR
STEP1- Getting Started
Understanding the Context
◉ What is the geographic area of interest?
○ Is it the immediate city limits?
○ City and suburbs around it?
○ A larger jurisdiction?

36.

IVHUB.IR
STEP1- Getting Started
Setting Goals and Objectives
◉ Typical performance criteria to achieve a rigorous
sample:
○ Data collection for no less than six months and no more than 12
○
○
○
○
○
○
○
months
Completing 14 sampling events per month
A minimum of 4 completed interviews per event
Completing 100% of sampling events
Complete ≥90% of the intercepts
Enroll ≥ 75% of the eligible men
Collect specimens with 80% of enrolled men
500 subjects total (or calculated sample size)

37.

IVHUB.IR
STEP1- Getting Started
Logistics and other considerations
◉ Logistics and other considerations
○
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Biological testing
Survey instruments
Ethical considerations.
Institutional Review Board Approval
Reimbursement for time and effort / Incentives
Operations Manual

38.

IVHUB.IR
STEP3-Formative Assessment / Community Buy In
◉ Define the community of interest
◉ Ways of accessing the community
◉ The attributes of the community relevant to
the specific public health issue
◉ Some of the tools of formative research
○ Secondary Data Review
○ Focus Groups

39.

IVHUB.IR
STEP4-Venue Univers
Sampling Frame Construction
◉
◉
Venue Identification (ID) Code
○
Example : E = Social organizations , 1st -> ID CODE = E001
Venue Eligibility
○
Any public or private locations attended by the priority population
Those excluded from monthly sampling frame :
○ Low levels of attendance of the priority population
○ lack of safety
○ disapproval by owners or managers

40.

IVHUB.IR
STEP4-Venue Univers
Venue Identification
◉
◉
◉
Venues and venue-day-time periods (VDTs)
Elicitation of Socio-demographic Characteristics &
Operational Barriers (Structural, Safety, Parking, Competing outreach
activities)
◉
Collaboration with Venue Owners/Managers &
Organizations
Enumeration
◉
Attendance Levels
○ Type I
○ Type II
○ Type III

41.

IVHUB.IR
Type I Enumeration
◉ Performed at all venues and is designed to
capture :
○ that the venue is attended by the population
○ days and times of high attendance (VDTs)
○ estimates of how many people attend during these
times
◉ Purpose : whether the venues gathered from
formative research are actual venues that the MARP
attends. ( observation)

42.

IVHUB.IR
Type I Enumeration Form

43.

IVHUB.IR
Type II Enumeration
◉
Performed at some venues and is designed to capture :
○
○
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○
○
◉
Venue identifiers
enumeration counts
intercepts eliciting key information from patrons that establish
membership in the priority MARP (e.g., gender, sexual behavior, IDU
behavior)
whether intercepted persons are potentially eligible for the study
general sense of where and what kind of enumeration area is best for
the venue
Purpose : determine the number of eligible persons who attend a
venue at a particular day and time period

44.

IVHUB.IR
Type II Enumeration Form

45.

IVHUB.IR
The criteria for including venues in the universe
◉ The minimum effective yield is set at 8
individual during a four hour period
◉ Only VDTs that yield more than 75% of the
target population

46.

IVHUB.IR
Example of Venue Universe

47.

IVHUB.IR
STEP5-Random selection
Sampling Calendar Creation

48.

IVHUB.IR
STEP5-Random selection
Sampling Calendar Creation
◉
◉
1. Block out staff days off (e.g., holidays) *
2. Schedule special events for the upcoming month
(e.g., gay pride parade) or “oneoff” events

49.

IVHUB.IR
STEP5-Random selection
Sampling Calendar Creation

50.

IVHUB.IR
STEP5-Random selection
Sampling Calendar Creation
Primary sampling venues :
Randomly select, without replacement, n venues (typically 14-16) – determined when setting
up performance criteria.
Arrange venues in order of least VDTs to most VDTs
Schedule least VDTs first moving through most VDTs
When venues has more than one VDT use dice (or other random selection method) to choose
which VDT to schedule. Schedule the randomly chosen VDT on the first available day of the
week.
Continue until all n (.e.g., 14-16) events are scheduled
Alternative sampling venues :
For each event, group or list venues which have VDTs starting within the time period of the
primary event
From this group choose, randomly without replacement, two alternate venues
Repeat 8 and 9 until each primary event has 2 alternate events
3.
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10.

51.

IVHUB.IR
STEP5-Random selection
Sampling Calendar Creation

52.

IVHUB.IR
Goals
◉ TLS approximates probability sampling method
(Cluster Sampling).
○ Randomizing VDTs
○ Systematic sampling at the venue itself
○ The length of time spent in the field conducting
sampling events

53.

IVHUB.IR
STEP5-Random selection
Practical considerations for the sampling calendar
◉
◉
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Sampling Event Conflicts
Canceling Events
Alternates
○ if there is a low traffic flow, staff must wait at least 30
minutes
Non-Random Events (Max 3 different Venuses per month)
Definitions of Traffic Flow ( in 15 min.)
○
○
○
Low flow = <20 clicked
Medium flow = 21-50 clicked
High flow = 50+ clicked

54.

IVHUB.IR
Step 6: Sampling Events / Recruitment
Key Activities during sampling events
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Enumeration – count all persons who cross into a recruitment area
Intercepts – approach and speak with designated persons
Eligibility – ask person questions to determine whether they are able to
participate
Enrollment – encourage person to enter into the study
Complete survey – take the participant through the entire survey
Counseling – provide information about HIV/STDs and appropriate
referrals
Specimen collection – collect blood, oral or other fluid for HIV/STD tests
Reimbursement/Incentives – pay participant for their time in cash,
vouchers/coupons, or tokens

55.

IVHUB.IR
Step 6: Sampling Events / Recruitment
Systematic Sampling
◉
◉
◉
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◉
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Enumerator counts every possible eligible person crossing
intercept area
Recruiters systematically approach enumerated persons
Recruiter introduces study, assesses interest, determines
eligibility, enrolls subject
When all recruiters are occupied, enumerator continues to count
When a recruiters is ready again, intercepts resume with the
next person
Enumerator can halt counting if problems arise
Enumeration ends when the four hour time-period is complete.

56.

IVHUB.IR
Step 6: Sampling Events / Recruitment
Setting Up an Enumeration Area

57.

IVHUB.IR
Step 6: Sampling Events / Recruitment
Strategies to successfully complete intercepts and enroll eligible subjects
When not try to recruit
◉ Safety concerns
◉ People walking too fast (marathon walker)
◉ People on cellular/mobile phones, MP3 players
◉ Physical gestures / Body language
◉ Too high or drunk
◉ Very firm refusal
○ If possible, get their reason for refusal
○ Inquire about participating later

58.

IVHUB.IR
Step 6: Sampling Events / Recruitment
Interview Options

59.

IVHUB.IR
Step 12: Analysis
Weighted Analysis
◉
TLS is held to approximate random sampling in that each
venue/VDT has an equal chance of inclusion
◉
Enough venues/VDTs sampled
◉
Weighting has not often been used
○ venues have shown high heterogeneity of attendees
○ key outcomes were not found to be associated with venues
○ TLS usually produces many small clusters rather than a few
large homogenous clusters minimize design effects

60.

IVHUB.IR
Step 12: Analysis
Weighted Analysis
◉ Probability Weight : Weighting can be achieved by
using the enumeration count of each event as the
basis for the weight.
◉ the ratio of the number of persons enrolled to the
number of eligible persons at each recruitment event.

61.

IVHUB.IR
Step 12: Analysis
Weighted Analysis

62.

IVHUB.IR
Step 12: Analysis
Cluster Analysis / Stratified Analysis
◉ Adjustment for Clustering - Statistical
software provides these adjustments by
designating the venue as the group or cluster.
◉ a venue is differently attended by very different
members of the MARP during specific day time
periods could be counted as a separate cluster

63.

◉
◉
◉
◉
◉
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•Internal validity strengthened by:
–High participation rate (performance goal: >75%)
–High eligibility assessment rate (>90%)
–High completion of VDT sampling events (>95%)
–No interviewer selection allowed
•Statistical analysis adjusts for venue attendance
pattern (relative representation) and homogeneity
within the venue (cluster)
◉ •External validity depends on good formative research

64.

◉
◉
◉
◉
◉
◉
◉
◉
◉
Typical performance criteria to achieve a rigorous sample:
–Data collection for no less than six months and no more than 12
months
–Completing 14 sampling events per month
–A minimum of 4 completed interviews per event
–Completing 100% of sampling events
–Complete ≥90% of the intercepts
–Enroll ≥ 75% of the eligible men
–Collect specimens with 80% of enrolled men
–500 subjects total (or calculated sample size)